A new length-based algebraic multigrid clustering algorithm

  • Authors:
  • L. Rakai;A. Farshidi;L. Behjat;D. Westwick

  • Affiliations:
  • Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada;Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada;Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada;Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada

  • Venue:
  • VLSI Design
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Clustering algorithms have been used to improve the speed and quality of placement. Traditionally, clustering focuses on the local connections between cells. In this paper, a new clustering algorithm that is based on the estimated lengths of circuit interconnects and the connectivity is proposed. In the proposed algorithm, first an a priori length estimation technique is used to estimate the lengths of nets. Then, the estimated lengths are used in a clustering framework to modify a clustering technique based on algebraic multigrid (AMG), that finds the cells with the highest connectivity. Finally, based on the results from the AMG-based process, clusters are made. In addition, a new physical unclustering technique is proposed. The results show a significant improvement, reductions of up to 40%, in wire length can be achieved when using the proposed technique with three academic placers on industry-based circuits. Moreover, the runtime is not significantly degraded and can even be improved.